Probabilistic inference is a key mechanism for reasoning about probabilistic programs.
Since exact inference is theoretically expensive, most probabilistic inference systems today …

We present techniques for the analysis of infinite state probabilistic programs to synthesize
probabilistic invariants and prove almost-sure termination. Our analysis is based on the …

Quantum computers promise dramatic advantages in processing speed over currently
available computer systems. Quantum computing offers great promise in a wide variety of …

This paper presents a new static analysis for deriving upper bounds on the expected
resource consumption of probabilistic programs. The analysis is fully automatic and derives …

We propose a framework to prove almost sure termination for probabilistic programs with
real valued variables. It is based on ranking supermartingales, a notion analogous to …

Termination is one of the basic liveness properties, and we study the termination problem for
probabilistic programs with real-valued variables. Previous works focused on the qualitative …

We propose an approach for the static analysis of probabilistic programs that sense,
manipulate, and control based on uncertain data. Examples include programs used in risk …

This article presents a wp--style calculus for obtaining bounds on the expected runtime of
randomized algorithms. Its application includes determining the (possibly infinite) expected …

We present a novel static analysis technique to derive higher moments for program
variables for a large class of probabilistic loops with potentially uncountable state spaces …

We consider the quantitative problem of obtaining lower-bounds on the probability of
termination of a given non-deterministic probabilistic program. Specifically, given a non …